{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "60761989",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import requests\n",
    "from  openai import OpenAI\n",
    "import gradio as gr\n",
    "import speech_recognition as sr\n",
    "import json\n",
    "from dotenv import load_dotenv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e0b6610a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OpenAI API Key exists and begins sk-proj-\n",
      "weather API Key exists\n"
     ]
    }
   ],
   "source": [
    "# Initialization\n",
    "\n",
    "load_dotenv(override=True)\n",
    "\n",
    "openai_api_key = os.getenv('OPENAI_API_KEY')\n",
    "weather_api_key = os.getenv('WEATHER_API_KEY')\n",
    "if openai_api_key:\n",
    "    print(f\"OpenAI API Key exists and begins {openai_api_key[:8]}\")\n",
    "else:\n",
    "    print(\"OpenAI API Key not set\")\n",
    "if weather_api_key:\n",
    "    print(\"weather API Key exists\")\n",
    "else:\n",
    "    print(\"weather API Key not set\")\n",
    "    \n",
    "MODEL = \"gpt-4o-mini\"\n",
    "openai = OpenAI()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "af9d2faf",
   "metadata": {},
   "outputs": [],
   "source": [
    "system_message = \"You are a helpful assistant for weather. \"\n",
    "system_message += \"You need to fetch the current, historical and forecast the weather data using weather api and provide the response\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "2c5208d8",
   "metadata": {},
   "outputs": [],
   "source": [
    "def fetch_current_weather(location):\n",
    "    url = f\"http://api.weatherapi.com/v1/current.json?key={weather_api_key}&q={location}&aqi=yes\"\n",
    "    return requests.get(url).json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8e6a12e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "def fetch_forecast_weather(location, days=3):\n",
    "    url = f\"http://api.weatherapi.com/v1/forecast.json?key={weather_api_key}&q={location}&days={days}&aqi=yes&alerts=yes\"\n",
    "    return requests.get(url).json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "eafc468e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def fetch_historical_weather(location, date):\n",
    "    url = f\"http://api.weatherapi.com/v1/history.json?key={weather_api_key}&q={location}&dt={date}&aqi=yes\"\n",
    "    return requests.get(url).json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2851ed55",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Weather function used as a tool by OpenAI\n",
    "def get_weatherapi_data(location, mode=\"current\", date=None, forecast_days=3):\n",
    "    if mode == \"current\":\n",
    "        return fetch_current_weather(location)\n",
    "    elif mode == \"forecast\":\n",
    "        return fetch_forecast_weather(location, days=forecast_days)\n",
    "    elif mode == \"historical\":\n",
    "        if not date:\n",
    "            # Default: yesterday\n",
    "            date = (datetime.date.today() - datetime.timedelta(days=1)).strftime(\"%Y-%m-%d\")\n",
    "        return fetch_historical_weather(location, date)\n",
    "    else:\n",
    "        return {\"error\": \"Unknown mode.\"}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "368176c2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Tool schema for OpenAI tool-calling\n",
    "weatherapi_tool_schema = [\n",
    "  {\n",
    "    \"type\": \"function\",\n",
    "    \"function\": {\n",
    "      \"name\": \"get_weatherapi_data\",\n",
    "      \"description\": \"Fetches current, forecast, or historical weather data from WeatherAPI.com for a given location.\",\n",
    "      \"parameters\": {\n",
    "        \"type\": \"object\",\n",
    "        \"properties\": {\n",
    "          \"location\": {\n",
    "            \"type\": \"string\",\n",
    "            \"description\": \"Name of the city, region, or coordinates.\"\n",
    "          },\n",
    "          \"mode\": {\n",
    "            \"type\": \"string\",\n",
    "            \"enum\": [\"current\", \"forecast\", \"historical\"],\n",
    "            \"description\": \"Type of weather data required.\"\n",
    "          },\n",
    "          \"date\": {\n",
    "            \"type\": \"string\",\n",
    "            \"description\": \"Date for historical data in YYYY-MM-DD format. Only needed if mode is 'historical'.\"\n",
    "          },\n",
    "          \"forecast_days\": {\n",
    "            \"type\": \"integer\",\n",
    "            \"description\": \"Number of forecast days (1-10). Only needed if mode is 'forecast'.\"\n",
    "          }\n",
    "        },\n",
    "        \"required\": [\"location\", \"mode\"]\n",
    "      }\n",
    "    }\n",
    "  }\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "bd9c4d38",
   "metadata": {},
   "outputs": [],
   "source": [
    "def audio_to_text(audio_filepath):\n",
    "    if audio_filepath is None or audio_filepath == \"\":\n",
    "        return \"\"\n",
    "    recognizer = sr.Recognizer()\n",
    "    try:\n",
    "        with sr.AudioFile(audio_filepath) as source:\n",
    "            audio = recognizer.record(source)\n",
    "        try:\n",
    "            transcript = recognizer.recognize_google(audio)\n",
    "            return transcript\n",
    "        except sr.UnknownValueError:\n",
    "            return \"\"\n",
    "        except sr.RequestError as e:\n",
    "            return f\"Speech recognition service error: {e}\"\n",
    "    except Exception as e:\n",
    "        return f\"Error opening audio file: {str(e)}\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "61c5de82",
   "metadata": {},
   "outputs": [],
   "source": [
    "def chat_agent(city, mode, date, forecast_days, audio=None):\n",
    "    user_query = city\n",
    "    if audio:\n",
    "        spoken_text = audio_to_text(audio)\n",
    "    print(\"Recognized speech:\", spoken_text)\n",
    "    if spoken_text and spoken_text.strip().lower() != \"flic en flac\":\n",
    "        user_query = spoken_text\n",
    "    else:\n",
    "        if not city.strip():\n",
    "            return \"Sorry, I could not recognize your speech. Please try again or type your city.\"\n",
    "\n",
    "    if not user_query.strip():\n",
    "        return \"Please provide a location by text or speech.\"\n",
    "\n",
    "    # Compose tool function arguments as the LLM would\n",
    "    args = {\n",
    "        \"location\": user_query,\n",
    "        \"mode\": mode\n",
    "    }\n",
    "    if mode == \"historical\" and date:\n",
    "        args[\"date\"] = date\n",
    "    if mode == \"forecast\":\n",
    "        try:\n",
    "            n_days = int(forecast_days)\n",
    "        except:\n",
    "            n_days = 3\n",
    "        args[\"forecast_days\"] = n_days\n",
    "\n",
    "    openai.api_key = openai_api_key\n",
    "\n",
    "    # LLM call for tool use\n",
    "    response = openai.chat.completions.create(\n",
    "        model=\"gpt-4-0613\",\n",
    "        messages=[{\"role\": \"user\", \"content\": f\"Get me {mode} weather for {user_query}\"+(f' on {date}' if date and mode==\"historical\" else \"\")+(f' for {forecast_days} days' if forecast_days and mode==\"forecast\" else \"\")}],\n",
    "        tools=weatherapi_tool_schema,\n",
    "        tool_choice={\"type\": \"function\", \"function\": {\"name\": \"get_weatherapi_data\", \"arguments\": json.dumps(args)}}\n",
    "    )\n",
    "    message = response.choices[0].message\n",
    "\n",
    "    if hasattr(message, \"tool_calls\") and message.tool_calls:\n",
    "        tool_call = message.tool_calls[0]\n",
    "        args2 = json.loads(tool_call.function.arguments)  # not really needed, already have args\n",
    "        location = args2.get(\"location\", user_query)\n",
    "        mode = args2.get(\"mode\", mode)\n",
    "        date = args2.get(\"date\", date)\n",
    "        forecast_days = args2.get(\"forecast_days\", forecast_days)\n",
    "        weather_data = get_weatherapi_data(location, mode, date, forecast_days)\n",
    "        tool_result = f\"Weather data (mode={mode}) for {location}:\\n{json.dumps(weather_data, indent=2)[:3000]}\"\n",
    "        followup = openai.chat.completions.create(\n",
    "            model=\"gpt-4-0613\",\n",
    "            messages=[\n",
    "                {\"role\": \"user\", \"content\": f\"Get me {mode} weather for {location}\"},\n",
    "                message,\n",
    "                {\n",
    "                    \"role\": \"tool\",\n",
    "                    \"tool_call_id\": tool_call.id,\n",
    "                    \"content\": tool_result\n",
    "                }\n",
    "            ]\n",
    "        )\n",
    "        answer = followup.choices[0].message.content.strip()\n",
    "        return answer\n",
    "    else:\n",
    "        return getattr(message, \"content\", \"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "44071389",
   "metadata": {},
   "outputs": [],
   "source": [
    "def update_date_visibility(mode):\n",
    "    return gr.update(visible=(mode==\"historical\"))\n",
    "\n",
    "def update_days_visibility(mode):\n",
    "    return gr.update(visible=(mode==\"forecast\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "618a5494",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "* Running on local URL:  http://127.0.0.1:7861\n",
      "* To create a public link, set `share=True` in `launch()`.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><iframe src=\"http://127.0.0.1:7861/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Recognized speech: Error opening audio file: FLAC conversion utility not available - consider installing the FLAC command line application by running `apt-get install flac` or your operating system's equivalent\n"
     ]
    }
   ],
   "source": [
    "with gr.Blocks() as demo:\n",
    "    gr.Markdown(\"## Weather Chat Agent (Current, Historical, Forecast)\")\n",
    "\n",
    "    with gr.Row():\n",
    "        city_input = gr.Textbox(label=\"City/Location\")\n",
    "        mode_input = gr.Dropdown(\n",
    "            [\"current\", \"historical\", \"forecast\"],\n",
    "            value=\"current\",\n",
    "            label=\"Weather Mode\")\n",
    "    with gr.Row():\n",
    "        date_input = gr.Textbox(label=\"Date for historical (YYYY-MM-DD)\", visible=False)\n",
    "        days_input = gr.Textbox(label=\"Forecast Days (for forecast)\", value=\"3\", visible=False)\n",
    "    audio_input = gr.Audio(type=\"filepath\", format=\"wav\", label=\"Or Speak your City/Location (optional)\")\n",
    "    output_box = gr.Textbox(label=\"Weather Info\", lines=8)\n",
    "    btn = gr.Button(\"Get Weather\")\n",
    "\n",
    "    # Show/hide date and days inputs based on dropdown\n",
    "    mode_input.change(update_date_visibility, mode_input, date_input)\n",
    "    mode_input.change(update_days_visibility, mode_input, days_input)\n",
    "    btn.click(\n",
    "        chat_agent,\n",
    "        [city_input, mode_input, date_input, days_input, audio_input],\n",
    "        output_box\n",
    "    )\n",
    "\n",
    "demo.launch()"
   ]
  }
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